scholarly journals Optimization of Tool Path Length on Three-Dimensional Drilling Application Using Ant Colony Algorithm

2021 ◽  
Vol 2129 (1) ◽  
pp. 012060
Author(s):  
Muhammad Danial Ikmal bin Rusman ◽  
Haslina Abdullah ◽  
Mohamad Shukri Zakaria ◽  
Norfazillah Talib ◽  
Lee Woon Kiow ◽  
...  
Keyword(s):  
Path Length ◽  
Ant Colony Algorithm ◽  
Tool Path ◽  
Block Design ◽  
Ant Colony ◽  
Drilling Process ◽  
Machining Time ◽  
Evaporation Coefficient ◽  
Simple Block ◽  
Complex Block

Abstract The lower machining time is important characteristic in the drilling machining process. Drilling process costs will increase if the machining time is high. Therefore, the main objective of this research is to develop Ant Colony Algorithm (ACO) to reduce the machining time by obtain the optimal tool path length. By using this algorithm, it can minimize the tool path length and significantly decreasing the machining time of drilling process. Simulating in 3-dimensional drilling on ACO has been constructed to minimize the shortest path of the drilling process. There are two type of workpiece has been used, which is simple block with 10 holes and complex block design that has 154 holes. ACO algorithm has been developed in Matlab R2017b to determine the optimal parameters of ACO of tool path length in drilling. Besides, simulation also has been done to investigate the effect of ACO parameter which is weight of pheromone (α), weight of trail (β), evaporation coefficient (e), and number of iterations. As a result, by define the parameter of iteration number at 900, the optimum parameter of weight of pheromone (α) is 5, weight of trail (β) is 4 and evaporation coefficient (e) is 0.4. Based on these parameters, the minimal tool path length obtain for simple and complex model are 286.965 mm and 6770.9860 mm respectively. Then, the result of tool path length of ACO simulation has been compared with the Mastercam outcome. ACO achieves a total tool path length of 286.965 mm while Mastercam achieved 569.878 mm for simple block design. Meanwhile, for complex block design, ACO produces a total tool path length of 6770.9860 mm while Mastercam has generate 55828.9050 mm of tool path length. By comparing these two approaches, ACO and Mastercam, ACO has that the short total tool path length by 49.64% on simple block design and 87.87% for complex block design.

TOOL PATH GENERATION OF CONTOUR PARALLEL BASED ON ANT COLONY OPTIMISATION

2016 ◽  
Vol 78 (6-9) ◽  
Author(s):  
Haslina Abdullah ◽  
Rizauddin Ramli ◽  
Dzuraidah Abd Wahab ◽  
Jaber Abu Qudeiri
Keyword(s):  
Path Length ◽  
Manufacturing Industry ◽  
Tool Path ◽  
Previous Method ◽  
Ant Colony ◽  
Numerical Control ◽  
Ant Colony Optimisation ◽  
Sharp Corner ◽  
Machining Time ◽  
Simulation Results

In today’s competitive market of manufacturing industry, shorter machining time is one of important factor for reducing the manufacturer’s cost. This paper presents the minimisation of machining time of computer numerical control (CNC) by eliminating the uncut region of sharp corner based on contour parallel milling method.  Each uncut region at sharp corner is represented by uncut line which consists of two nodes in x and y directions.  An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. The optimisation of tool path length based on ACO algorithm ascertained that the cutting tool remove the uncut line once and able to eliminate the uncut region in the shortest tool path length. To observe the effectiveness of the ACO performance, the simulation results are compared with the results obtained by the previous method.  Finally the simulation results show the reduction of 5% machining time compared to previous method.

scholarly journals An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Jiang Zhao ◽  
Dingding Cheng ◽  
Chongqing Hao
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Selection Strategy ◽  
Planning Problem ◽  
Evaporation Coefficient ◽  
Mobile Vehicle ◽  
Starting Point ◽  
Path Planning Problem ◽  
Improved Ant Colony Algorithm

This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle. The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles. Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle. And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search. The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm. In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability. Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

Application of Ant Colony Algorithm Based on Optimization Parameters in Equipment Material Transport

2013 ◽  
Vol 756-759 ◽  
pp. 3487-3491
Author(s):  
Xi Li ◽  
Li Yun Chen ◽  
Ai Zhen Liu ◽  
Sen Liu
Keyword(s):  
Genetic Algorithm ◽  
Path Length ◽  
Ant Colony Algorithm ◽  
Computation Time ◽  
Path Selection ◽  
Ant Colony ◽  
Performance Parameters ◽  
Material Transport ◽  
Optimization Parameters

In order to solve the path selection problem in the transport of equipment and materials, while improving the quality of solutions, this paper uses ant colony algorithm based on optimization parameters to achieve. Through genetic algorithm to solve the parameters of ant colony algorithm, resulting in a better performance parameters. The experimental results show that ant colony algorithm based on optimization parameters has been improved on path length and computation time than the traditional ant colony algorithm.

scholarly journals Path Planning Algorithm for Mobile Robot Based on Improved Ant Colony Algorithm

2021 ◽  
Vol 2083 (4) ◽  
pp. 042033
Author(s):  
Yanyun Li ◽  
Fenggang Liu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Path Length ◽  
Ant Colony Algorithm ◽  
Planning Process ◽  
Optimal Path ◽  
Ant Colony ◽  
Position Information ◽  
Environment Model ◽  
Planning Algorithm

Abstract Due to the influence of full traversal environment, the path length obtained by existing methods is too long. In order to improve the performance of path planning and obtain the optimal path, a full traversal path planning method for omnidirectional mobile robots based on ant colony algorithm is proposed. On the basis of the topology modeling schematic diagram, according to the position information of the mobile robot in the original coordinate system, a new environment model is established by using the Angle transformation. Considering the existing problems of ant colony algorithm, the decline coefficient is introduced into the heuristic function to update the local pheromone, and the volatility coefficient of the pheromone is adjusted by setting the iteration threshold. Finally, through the design of path planning process, the planning of omnidirectional mobile robot’s full traversal path is realized. Experimental results show that the proposed method can not only shorten the full traversal path length, but also shorten the time of path planning to obtain the optimal path, thus improving the performance of full traversal path planning of omnidirectional mobile robot.

scholarly journals Development of Direction-Parallel Strategy for Shorting A Tool Path in The Triangular Pocket Machining

2019 ◽  
Vol 18 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Mochammad Chaeron ◽  
Budi Saputro Wahyuaji ◽  
Apriani Soepardi
Keyword(s):  
Path Length ◽  
Tool Path ◽  
Machining Efficiency ◽  
Machining Time ◽  
Pocket Machining ◽  
Direction Parallel ◽  
Numerical Examples ◽  
Tool Paths ◽  
Machining Strategy ◽  
Parallel Strategy

The machining strategy is one of the parameters which practically influences the time of the different manufacturing geometric forms. The machining time directly relates to the machining efficiency of the tool paths. In area milling machining, there are two main types of tool path strategies: a direction-parallel milling and contour-parallel milling. Then direction-parallel milling is simple compared with a contour-parallel strategy. This paper proposes a new model of the direction-parallel machining strategy for triangular pockets to reduce the tool path length. The authors develop an analytical model by appending additional the tool path segments to the basis tool path for cutting un-machined area or scallops, which remained along the boundary. To validate its results, the researchers have compared them to the existing model found in the literature. For illustrating the computation of this model, the study includes two numerical examples. The results show that the proposed analytic direction-parallel model can reduce the total length of machining. Thus, it can take a shorter time for milling machining.

Minimizing the Energy Consumption of Holes Machining Integrating the Optimization of Tool Path and Cutting Parameters on CNC Machines

2021 ◽  
Author(s):  
Chunhua Feng ◽  
Xiang Chen ◽  
Jingyang Zhang ◽  
Yugui Huang ◽  
Zibing Qu
Keyword(s):  
Energy Consumption ◽  
Path Planning ◽  
Ant Colony Algorithm ◽  
Tool Path ◽  
Cutting Parameters ◽  
Multi Objective Optimization ◽  
Tool Path Planning ◽  
Machining Time ◽  
Cnc Machines ◽  
Multi Objective

Abstract The application of sustainable manufacturing technologies is the new challenge faced by enterprises, industries, and researchers under the background of supporting carbon peak and carbon neutral. This paper studies how to reduce the energy consumption of holes machining through optimizing tool path and cutting parameters simultaneously. The integrated optimization methodology can further reduce the energy consumption comparing with optimizing the tool path or cutting parameters separately. Firstly, the energy model of holes machining is established based on machine tools’ energy composition, tool path planning, and process parameters. Due to tool path planning as air cutting process has big relationship with reducing energy, especially for holes group with a big proportion in the whole process. The tool path of holes processing is optimized by the improved ant colony algorithm to solve the issue considering the distance from one hole to the next hole. Based on this optimized path, a multi-objective optimization model for hole cutting parameters is established, considering the spindle speed and feed rate as the optimization variables and machining time, energy consumption, and surface roughness as the objective function. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) is employed to solve the multi-objective optimization problem of holes machining. The case study with 50 holes is used to testify the application of the proposed method to provide the practical energy efficiency strategy for holes group or multi-hole parts on CNC machines assisting in achieving sustainable production in manufacturing sectors.

Research on Vehicle Routing Optimization Based on Improved Ant Colony Algorithm

2013 ◽  
Vol 385-386 ◽  
pp. 1917-1920
Author(s):  
Rui Wang ◽  
Zai Tang Wang
Keyword(s):  
Vehicle Routing ◽  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Route Optimization ◽  
Local Optimum ◽  
Evaporation Coefficient ◽  
Logistics Distribution ◽  
Routing Optimization ◽  
Vehicle Routing Optimization

This paper analyzes the domestic and international logistics distribution route optimization problem and the research status of ant colony algorithm, illustrates the problems existing in the logistics distribution now. It reflects the necessity to research on the vehicle routing optimization problem. In order to increasing the ant colony algorithm’s convergence speed and avoiding to fall into local optimum, we improve the pheromone evaporation coefficient and visibility to optimize the searching ability, which can avoid premature convergence and stagnation.

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